Notice Board :

Call for Paper
Vol. 6 Issue 11

Submission Start Date:
Nov 01, 2019

Acceptence Notification Start:
Nov 10, 2019

Submission End:
Nov 15, 2019

Final MenuScript Due:
Nov 28, 2019

Publication Date:
Nov 30, 2019
                         Notice Board: Call for PaperVol. 6 Issue 11      Submission Start Date: Nov 01, 2019      Acceptence Notification Start: Nov 10, 2019      Submission End: Nov 15, 2019      Final MenuScript Due: Nov 28, 2019      Publication Date: Nov 30, 2019




Volume V Issue XII

Author Name
Rachana Barfa, Pratibha Nagaich
Year Of Publication
2018
Volume and Issue
Volume 5 Issue 12
Abstract
The environment in which a MANET is placed has a significant impact on the success of the routing strategy. Therefore, we chose to base our concepts and analysis on the assumption that we must support what is arguably the most demanding MANET environment, a tactical military environment. Many routing protocols for such networks have been proposed so far. Amongst the most popular ones are Dynamic Source Routing (DSR), Ad hoc On-demand Distance Vector (AODV), Destination-Sequenced Distance-Vector Routing (DSDV) and Optimized Link State Routing (OLSR). This paper contains the performance enhancement of routing protocols. Our observations regarding the behavior of the above protocols, in large-scale Mobile Ad hoc Networks (MANETs) and from the analysis it is clear that the optimized link state algorithm to send data to the leader proof to offer more reduced drop packets and also increase the lifetime of the network. Based on the analysis of this simulation results, OLSR protocol offer a be
PaperID
2018/IJTRM/12/2018/21268

Author Name
Manish Porwal, Abhishek Raghuvanshi
Year Of Publication
2018
Volume and Issue
Volume 5 Issue 12
Abstract
The capacity to screen the advancement for students’ academic execution is a basic issue of the academic Group from claiming higher Taking in. An arrangement to dissecting students’ comes about dependent upon group dissection and utilization standard measurable calculations with organize their scores information as stated by the level about their execution may be portrayed. In this paper, we also actualized k-mean and K-Medoids grouping algorithm for examining students’ consequence information. Those model might have been consolidated for those deterministic model should dissect those students’ effects of a private foundation clinched alongside % Iberia which is a great standard with screen the progression of academic execution about people for higher institutional to the reason for making an successful choice by those academic organizers.
PaperID
2018/IJTRM/12/2018/21270

Author Name
Saraswati Sharma, Prof. Namrata Sharma
Year Of Publication
2018
Volume and Issue
Volume 5 Issue 12
Abstract
Wireless Sensor Networks consist of small wireless nodes which are capable of sensing, computation, and wireless communication capabilities. The main constraint associated with wireless sensor network design is that sensor nodes operate with limited energy budget. The efficient utilization of energy source in a sensor node is very important criteria to elongate the life-time of WSN. Wireless sensor networks have explored to many protocols specifically designed for sensor networks where energy consideration is very crucial. There are several energy efficient reactive routing protocols among this, AODV is a protocol. This thesis is intended to introduce energy-efficient routing protocol, known as MAODV, which is extended version of AODV to enhance energy-efficiency, lifetime in WSN. We have simulated AODV and MAODV in Network simulator-2 (NS2) and analyzed performance in terms of residual energy, throughput and network life time.
PaperID
2018/IJTRM/12/2018/21272

Author Name
Amit Swami, Nilay Khare
Year Of Publication
2018
Volume and Issue
Volume 5 Issue 12
Abstract
Artificial neural network is an information processing system which is inspired by biological neural system. It is widely utilized because of its competency to derive consequential information from complex data, adaptive learning, self organization and real time operation. One of the most promising task of neural network is classification and prediction. The extreme learning machine (ELM) has attracted much attention over the past decade due to its fast learning speed and convincing generalization performance.ELM, a single layer feed forward network is used for this purpose because of its advantage over conventional neural network; i.e. better generalization performance. Depending on the types of activation functions used in ELM structure, the performance of the network varies. This paper proposes new activation function and comparison study is performed using ELM for different activation functions.
PaperID
2018/IJTRM/12/2018/21274